No Taxation without Information: Deterrence and Self ... · No Taxation without Information: Deterrence ... 1Information constraints have been a key feature of models in the optimal

American Economic Review 2015, 105(8): 2539–2569 http://dx.doi.org/10.1257/aer.20130393

2539

No Taxation without Information: Deterrence and Self-Enforcement in the Value Added Tax†

By Dina Pomeranz*

Claims that the VAT facilitates tax enforcement by generating paper trails on transactions between firms contributed to widespread VAT adoption worldwide, but there is surprisingly little evidence. This paper analyzes the role of third-party information for VAT enforce-ment through two randomized experiments among over 400,000 Chilean firms. Announcing additional monitoring has less impact on transactions that are subject to a paper trail, indicating the paper trail’s preventive deterrence effect. This leads to strong enforcement spillovers up the VAT chain. These findings confirm that when taking evasion into account, significant differences emerge between other-wise equivalent forms of taxation. (JEL D83, H25, H26, K34, O17)

A fundamental constraint for taxation is that governments need to be able to observe transactions in order to impose a tax on them. A growing literature there-fore argues that understanding information flows is central to effective taxation. When governments imperfectly observe transactions, important differences emerge between forms of taxation that are equivalent in standard models of taxation but differ in the information they generate for the government (Slemrod 2008).1 Third-party reporting, verifiable paper trails, and whistle-blowers are thought to play an important role in facilitating tax enforcement (Kopczuk and Slemrod 2006; Kleven, Kreiner, and Saez 2009; Kleven et al. 2011; Kumler, Verhoogen, and Frías 2013). The challenge of enforcing taxation is particularly severe in developing countries, where many transactions in the economy are not readily observable by the govern-ment, and it has been argued that these limited sources of information can explain

1 Information constraints have been a key feature of models in the optimal taxation literature as well. While ability is not observable in these models, most transactions in the economy are typically assumed to be observable.

* Harvard Business School, Harvard University, Boston, MA 02163, and NBER (e-mail: [email protected]). I thank Alberto Alesina, Samuel Asher, Martin Besfamille, Lorenzo Casaburi, Raj Chetty, David Cutler, Oeindrila Dube, Martin Feldstein, Brigham Frandsen, Edward Glaeser, Dominik Hangartner, Lakshmi Iyer, Kelsey Jack, Matthew Gentzkow, Louis Kaplow, Felipe Kast, Lawrence Katz, Henrik Kleven, Wojciech Kopczuk, Michael Kremer, Josh Lerner, Jeffrey Liebman, Stephan Litschig, Isaac Mbiti, Stephan Meier, Sendhil Mullainathan, Paul Niehaus, Suresh Naidu, Giacomo Ponzetto, Joel Slemrod, Matthew Weinzierl, Justin Wolfers, Danny Yagan, Tristan Zajonc, participants at various seminars and conferences, and three anonymous referees for helpful comments. I am exceedingly grateful to the Chilean Tax Authority for outstanding collaboration and funding of the implementation and to the Swiss Study Foundation, the David Rockefeller Center for Latin American Studies, and the Project on Justice Welfare and Economics for research and travel grants that made this project possible.

† Go to http://dx.doi.org/10.1257/aer.20130393 to visit the article page for additional materials and author disclosure statement.

2540 THE AMERICAN ECONOMIC REVIEW AUGUST 2015

some of the key differences in tax systems between developed and developing coun-tries (Gordon and Li 2009; Besley and Persson 2013).2

The Value Added Tax (VAT) is a stark example of a tax believed to facilitate enforcement through a built-in incentive structure that generates a third-party reported paper trail on transactions between firms, which makes it harder to hide the transaction from the government (e.g., Tait 1972; Burgess and Stern 1993; Agha and Haughton 1996; Kopczuk and Slemrod 2006). This belief contributed to one of the most significant developments in tax policy of recent decades (Keen and Lockwood 2010): a striking increase in VAT adoption from 47 countries in 1990 to over 140 today (Bird and Gendron 2007). There is, however, surprisingly little evidence eval-uating these self-enforcing properties of the VAT.

This paper investigates the role of third-party reported paper trails for tax enforce-ment, and tests for the self-enforcing properties in the VAT through two randomized field experiments with over 445,000 firms in Chile. A first experiment, the large-scale Letter Message Experiment, evaluates the effects of the VAT paper trail across the entire economy in a fully developed VAT system. It investigates whether the VAT paper trail lowers the tax payment response to an increase in the perceived audit probability of randomly chosen firms. This would suggest that the paper trail has a preventive deterrence effect on evasion. Since a paper trail facilitates detection of evasion during the audit, one would expect firms to respond more to an increase in the audit probability where a paper trail is present, if evasion levels are equal across transactions. Observing that a given firm responds less on its transactions that are covered by a paper trail therefore suggests that the preventive deterrence effect of the paper trail was strong enough to reduce evasion to the point where an increase in the audit probability has a smaller effect. The experiment exploits the fact that the incentive structure built into the VAT system, which generates the paper trail, breaks down at the final production stage, where sales are made to consumers, rather than other firms: while it is in firms’ interest to ask suppliers for receipts in order to deduct input costs from their VAT bill, consumers have no incentive to do so.

The Chilean Tax Authority sent letters indicating an increased audit probability to over 100,000 randomly selected firms. While the letters generate an immediate and strong increase in VAT payments, this effect is much weaker on transactions between firms, where the paper trail is present, than on sales to final consumers, where there is no VAT paper trail. This holds true not only when comparing between firms with different shares of final sales, but also when comparing the response of different types of transactions within a given firm. Consistent with a model by Kleven, Kreiner, and Saez (2009) about the impact of firm size on evasion, small firms respond more to the deterrence message. There is suggestive evidence that a substantial fraction of the higher response in smaller firms may be driven by their higher propensity to sell at the retail level, where the VAT paper trail is absent.3

2 Tax evasion is a fundamental challenge for developing countries, where on average, the informal sector rep-resents about 40 percent of GDP, ranging up to 70 percent (Schneider, Buehn, and Montenegro 2010). High evasion rates can not only severely restrict funding for basic public infrastructure, they can also lead to significant distor-tions in the economy. Even in the United States, overall tax evasion is estimated to be around 16 percent (Internal Revenue Service 2008), a loss similar in size to the entire corporate income tax.

3 In order to test whether the impact of the letter really stems from deterrence, I also compare its effect to both a motivational letter that appeals to tax morale and social norms, and a placebo letter that contains information that is irrelevant for tax compliance. The methodology of analyzing the impact of different letter messages on tax payments

2541Pomeranz: no TaxaTion wiThouT informaTion VoL. 105 no. 8

Conceptually, this type of intervention represents an indirect use of randomized experiments, as defined by Khwaja and Mian (2011). It allows studying an existing policy at a large scale, even if the policy itself cannot be randomized. The idea is to test whether randomly induced variation of another factor that interacts with the pol-icy (in our case the perceived audit probability) generates the response that would be predicted based on the underlying mechanism if the policy is effective. The two experiments provide both types of interventions in the classification of Ludwig, Kling, and Mullainathan (2011). The Letter Message Experiment is a (indirect) policy evaluation aimed at testing whether the policy works on a nationwide level, while the second experiment, the Spillover Experiment, is a mechanism experiment aimed at showing the underlying mechanism that leads the policy to be effective.

The Spillover Experiment was designed to find direct evidence for the self-en-forcing mechanism that underlies the findings of the Letter Message Experiment. It examines the transmission of tax enforcement through the VAT paper trail up the production chain. The idea is to jump-start the effect in a sample where it is not cur-rently well enforced, by injecting deterrence into the system and observing how it propagates along the paper trail and up the production chain. Half of a selected sam-ple of firms suspected of tax evasion was randomly selected to receive an announce-ment of an upcoming audit. The whole sample was later summoned for an audit, and for the 1,527 firms that the tax authority was able to audit, information about their pretreatment trading partners was collected.4 The randomly administered audit announcement leads to strong spillover effects that increase VAT payments by the suppliers of the treated firms. In line with the asymmetric incentives between clients and suppliers in the self-enforcing mechanism of the VAT, tax payments of client firms do not increase.

Taken together, the two experiments show that for a given firm, the VAT paper trail acts as a substitute to the firm’s own audit probability, and globally the paper trail acts as a complement to the audit probability, since its effectiveness gets multi-plied through the spillover effects. This represents the first micro-empirical evidence for the self-enforcing properties of the VAT. Previous evidence has been limited to cross-country comparisons, investigating whether countries that adopt a VAT subse-quently raise more taxes (e.g., Nellor 1987; Ebrill et al. 2001).These findings pro-vide the first evidence of how tax enforcement generates spillovers through firms’ trading networks and, together with Rincke and Traxler (2011), they represent one of the first documentations of spillovers in tax enforcement overall. The results imply that when choosing an optimal audit strategy, a tax authority may not only want to consider the expected deterrence effect on the audited firm, but also the multiplier effect through the firm’s trading network.

This paper also provides evidence for a larger, mostly theoretical literature on the importance of information and third-party reporting for effective taxation, par-ticularly in developing countries (e.g., Kopczuk and Slemrod 2006; Gordon and Li 2009; Kleven, Kreiner, and Saez 2009). Because evasion is by its nature difficult

was first developed by Slemrod, Blumenthal, and Christian (2001), and has recently been employed by a growing number of researchers and tax authorities to shed light on the impact of deterrence and motivational appeals of tax payments by individuals mostly in developed countries (see Hallsworth 2014 for an overview).

4 For a discussion of attrition at the auditing stage, see Section IIC.


to detect, and micro-level tax data is highly confidential, there has been a dearth of micro-empirical evidence (Slemrod and Yitzhaki 2002). One notable exception is an intervention conducted concurrently to this field experiment by Kleven et al. (2011), who analyze the individual income tax in Denmark and formalize the distinction between third-party and self-reported income. They find that evasion is generally low, except for the small fraction of income for which the government does not already possess third-party reported information. These results confirm related find-ings for the income tax on a more aggregate level by the US Taxpayer Compliance Measurement Program (TCMP) (Internal Revenue Service 1996, 2006).5

The paper extends the findings of this literature in several ways. First, it looks at tax compliance by firms rather than individuals. Raising and enforcing tax pay-ments from firms strongly reduces the number of agents the tax authorities must oversee (Kopczuk and Slemrod 2006), and thus may be a more feasible approach for developing countries to increase tax revenue. Firms can play an important role of aggregators of information that facilitate tax enforcement. Second, it analyzes tax compliance in a developing country context. Evasion rates are much higher in poorer countries, and while there is a growing empirical literature investigating tax-ation in such contexts (e.g., Engel, Galetovic, and Raddatz 1998; Fisman and Wei 2004; Olken and Singhal 2011; Carrillo, Emran, and Rivadeneira 2012; Kleven and Waseem 2012; Kumler, Verhoogen, and Frías 2013; Naritomi 2013), there is still little micro-empirical evidence.

Third, the findings speak to the interplay of information with deterrence in tax enforcement. In the sample of the Spillover Experiment, prior to the audit announce-ment, self-enforcement was incomplete at best. The deterrence effect from the audit announcement was necessary to trigger the effectiveness of the paper trail, showing that it is the interaction of information with deterrence that leads to effective tax enforcement. Finally, and particularly relevant for developing countries, the paper finds that third-party records strongly affect tax compliance even in a context where they are not automatically accessible to the tax authority.6

The remainder of this paper is structured as follows: Section I provides back-ground on the VAT in Chile and on the mechanism of the self-enforcement hypoth-esis of the VAT, Section II describes study design, data and estimation strategy, and Section III shows the results of the Letter Message Experiment and the Spillover Experiment in turn. Section IV concludes.

I. Context

A. Background on the VAT and Its Use in Chile

A large majority of countries around the world have a VAT, and for many devel-oping countries it represents the largest source of tax revenue. In Chile, the VAT

5 Alm, Deskins, and McKee (2009) study a related question in a lab setting, by experimentally varying the por-tion of an individual’s income that is subject to third-party reporting, and find that cheating increases as individuals earn larger shares of income that are not perfectly detectable.

6 For most transactions in Chile, as in many developing countries, records are kept in handwritten books. The tax authority can verify them during audits, but in contrast to many developed countries, these records are not available in electronic form for automatic cross-checks.


accounts for about half of tax revenues (Servicio de Impuestos Internos 2010a). Chile has a single 19 percent VAT rate, which is paid monthly. Firms pay VAT on the difference between total sales and total input costs. The overall tax base—total value added in the production chain—is therefore equivalent to that of a sales tax, which is paid on the entire final value at the retail stage.7 The main difference between a VAT and a retail sales tax lies in the way it is collected and in who remits the tax to the government. This difference is irrelevant in most standard tax models, but is thought to have significant implications when taking tax administration and tax evasion into account (Slemrod 2008).

Firms have to document their declared amounts of “tax debit” (sales and other sources of revenue) and “tax credit” (input costs) with the original receipts.8 If the tax credit is greater than the debit for a given month, the excess can be carried over to the following month as a credit (Servicio de Impuestos Internos 2011). Firms are allowed to claim rebates, but in practice few do so as it is time consuming and triggers an automatic audit.

A firm’s book of purchases therefore contains documentation about the sales of its suppliers. This leads to the third-party paper trail along the production chain —henceforth, “paper trail”—which allows the tax authority to cross-check the two firms’ records against each other. In Chile, as in many countries, most firms do not have to submit this information to the tax authority. Only very large firms, and what was at the time of the study a small number who choose to use an online fil-ing system, do so. For all other firms, this information can be accessed by the tax authority through an audit, but not as a matter of routine. For this reason, the tax authority does not generally know which firms trade with one another. The Spillover Experiment was therefore designed to collect such information.

To prevent fraudulent production of fake input receipts or duplications, all receipts have to be preapproved and stamped by the Chilean tax authority. These receipts are numbered so that missing sales receipts must be explained at audit. The tax authority uses the part of the cross-checkable information that it has on file (i.e., sales and purchases of large firms and firms that use electronic accounting, as well as information from previous audits) to calculate whether tax declarations display discrepancies with third-party reported information. This calculation is performed both for the annual income tax returns and monthly VAT returns. Letters are sent to the taxpayers with the largest discrepancies (about 50,000 per year), requiring them to explain or correct the situation. Outstanding tax refunds are withheld until that situation has been resolved. Tax officials also regularly visit all retail stores to check that the books are well-kept and that correct receipts are given to customers.

Official estimates of VAT evasion in Chile, based on the comparison of collected VAT to aggregate consumption data from the central bank, have ranged between 27 percent and 12 percent since 1990, with significant fluctuations from one year to the next (Servicio de Impuestos Internos 2010b). Only a few industries are exempt

7 This equivalence holds when the VAT has a uniform rate and no exemptions. 8 This collection method is commonly known as the “credit-invoice method.” The vast majority of countries

with a VAT currently use the credit-invoice method with a few exceptions, such as Japan that uses the subtraction method (Grinberg 2010).


and there is no minimum size threshold for firms to be subject to the VAT.9 This context allows for analysis of the VAT across a large set of different firm types, with-out the interference of confounding institutional factors such as industry-specific exemptions or varying VAT rates.

B. Mechanism of the “Self-Enforcing” Properties of the VAT

The “self-enforcement” hypothesis in the VAT is based on the premise that firms have an incentive to ask their suppliers for receipts because they can deduct input costs from their VAT bill (Agha and Haughton 1996). This incentive builds the cre-ation of paper trails directly into the tax structure. Since the amounts are recorded in two sets of books, the risk of cross-checks is thought to deter firms from report-ing differing amounts (Bird and Gendron 2007). The buyer acts as the third-party, recording a transaction which creates a liability for the supplier. There is no scope for gains from collusion between two parties in the middle of the VAT chain since the two sides of a transaction in inter-business trade have opposing incentives: the buyer benefits from overstating the input cost, while the seller benefits from under-stating the sale. This mechanism breaks down at the end of the chain, since the final consumer has no incentive to ask for a receipt.10

To illustrate, let us index the firms along the value chain by i ∈ 1, 2, … N , where N is the final firm in the production chain; denote by c ˆ i and s ˆ i the reported amount of input costs and sales of firm i respectively, and denote by c i and s i the actual amounts. On a trade between two firms, i and i + 1 , firm i + 1 would want a receipt from firm i in order to be able to deduct firm i ’s sale s i from its input costs c i+1 . The key assumption behind the notion that “self-enforcement” breaks down at the retail stage is that all else equal, the cost of evasion will be lower at that point than in the middle of the production chain because firm N is not faced by a firm N + 1 that would want a receipt. Instead, firm N is faced by a consumer who does not require the receipt. In this case, no collusion is required to omit the declaration of sales by firm N.

There are several reasons why this self-enforcing mechanism might not work in practice. First, as mentioned above, most firms do not have to report this third-party information directly to the government. The self-enforcing mechanism depends on the deterrence effect of a cross-check conducted during a possible audit. The word “self-enforcement” is therefore misleading, since it can be expected to work only in interaction with credible deterrence on the part of the tax authority. Second, since the mechanism breaks down at the final stage, it can potentially unravel from the bottom if collusion builds up from the final stage.

If the mechanism works, we would expect a preventive deterrence effect on trans-actions covered by the paper trail. This will affect how firms respond to an increased audit probability in the following way. The information contained in the paper trail

9 Only the following entities are VAT exempt: news organizations, transportation, education, public universities and hospitals, the central bank, the social security administration, the ministry of national defense, the national postal services, and the public lottery. As is usual, exports are VAT free.

10 For this reason, several countries have tried to increase the incentive for the consumer by imposing fines for consumers who do not ask for a receipt, organizing lotteries with consumer receipts, allowing consumers to deduct part of their VAT payments from the income tax, etc. (Naritomi 2013).


facilitates detection of evasion during an audit. At a given level of evasion, one would therefore expect firms to respond more to an increased audit risk on trans-actions with a paper trail. The anticipation of this ease of detection can lead firms to reduce evasion ex ante on transactions with a paper trail. If this preventive deter-rence effect is strong enough, it may reduce evasion to the point where an increase in the audit probability has a smaller effect on transactions covered by a paper trail (as there is less evasion on these transactions to begin with). At that point, the paper trail and the audit probability will interact in a substitutive way.

Observing firms responding less on transactions with a paper trail therefore suggests that ex ante evasion was lower on these transactions. The Letter Message Experiment tests whether this is the case.11 The Spillover Experiment complements the findings of the Letter Message Experiment by showing the mechanism by which the preventive deterrence effect comes about.

We can distinguish two forms of VAT evasion on inter-firm transactions, and spill-over effects can operate for both. “Unilateral evasion” occurs when a paper trail is created but firms take the risk of underreporting their tax obligation despite the fact that this leads to discrepancies between the amounts reported by the buyer and sell-er.12 This is based on the hope that the tax authority will not cross-check the records. It does not require any coordinated actions between buyer and seller. Through “col-lusive evasion” a transaction is either completely omitted from the books of both the seller and the buyer or underreported (with the reported amount matching across the two books). This requires collusion, and as discussed above, reduces overall VAT payments if it is carried through to the end of the production chain.

Expressed in the notation introduced above firm i can be involved in unilat-eral VAT evasion in two ways: c ˆ i > c i or s ˆ i < s i , which correspond to c ˆ i > s ˆ i−1 and s ˆ i < c ˆ i+1 respectively. Collusive evasion implies: c ˆ i ≠ c i but c ˆ i = s ˆ i−1 , or s ˆ i ≠ s i but s ˆ i = c ˆ i+1 . In order for a collusive equilibrium to be incentive compat-ible, it must be the case that c i − c ˆ i ≤ s i − s ˆ i . Intuitively, sales under-reporting must be greater than cost underreporting for this to be beneficial to the firm. As discussed above, there is no scope for collusion in the middle of the chain due to the fact that firms have opposing incentives in reporting transactions. Collusive evasion must flow up the chain from a firm, which can unilaterally evade taxes. If firm n engages in collusive evasion, then s i ˆ < s i and c ˆ i < c i for all i ≥ n up to N within the chain of firms engaged in collusive evasion.

Let us now analyze what happens to spillovers for both unilateral and collusive evasion if monitoring is increased with a preannouncement for firm n at some point within the production chain. In the case of unilateral evasion, the spillovers are sym-metric for suppliers and clients. These spillovers act through information: upstream and downstream firms may learn about the audit preannouncement that firm n received. They may thus update their priors about the probability that their receipts from trades with firm n will be cross-checked against firm n’s receipts or that they

11 As discussed in more detail in the results section, the necessary assumption is that a lower response is not driven by other differences within firms for the type of transactions covered by a paper trail.

12 In order to reduce tax liability, the seller will tend to understate the value of a transaction, while the buyer will tend to inflate it.


will be audited themselves. This may lead them to revise their declared transactions to be consistent with those of firm n , thereby reducing evasion.

In the case of collusive evasion, an increase in the audit probability of firm n increases the likelihood that it will insist that the transactions with its trading part-ners be “on the books.” Hence, the audit preannouncement can lead to the cre-ation of a paper trail. Suppose firm n , which is in the interior of a colluding chain i, i + 1, … , N , is sent an audit preannouncement. If firm n starts to create a paper trail, this can hurt its supplier firm n − 1 , as it may cause that firm to increase its declared sales and ultimately its tax liability. Firm n − 1 may react by simultane-ously increasing its declared inputs as well, which may hurt firm n − 2 in turn. So the collusion may break all the way upstream. We move from a collusive equilib-rium between firms i, i + 1, … , N to a new partially collusive equilibrium between firms n + 1, … , N .

The increase in declared sales by firm n benefits the client firm, n + 1 , which can now declare higher input costs. Thus the client firm can report a lower tax liability.13 These asymmetric effects are illustrated in Table 1. Reducing collusive evasion by firm n in the middle of the chain does not necessarily increase total government tax revenue. Instead it may simply lead to a transfer from firm n and those upstream of it to those downstream of it. This mirrors the difficulty of evading the VAT through collusion: collusive evasion in the VAT that is not combined with unilateral evasion at the retail stage or in the middle of the chain, simply leads to transfers between firms along the chain, rather than to an increase in overall evasion.

Taking both types of evasion together, the effect of an increase in the audit probability on reported tax liability is positive for suppliers and ambiguous for clients, depending on which type of inter-firm evasion dominates. The Spillover Experiment tests whether increasing a firm’s audit probability indeed increases VAT payments by its trading partners, and whether this effect is asymmetrically concentrated on its suppliers.

13 Depending on the bargaining between firms n + 1, … , N , some of this gain may be passed down the value chain by n + 1 reporting higher sales so that firm n + 2 can report higher input costs, etc.

Table 1—Responses to Increase in Audit Probability: Collusive and Unilateral Evasion

Position in supply chain Collusive evasion Unilateral evasion

Supplier Sales ↑ VAT ↑ Sales ↑ VAT ↑

Treated firm Inputs ↑ VAT ( ↑ ) Inputs ↓ VAT ↑ Sales ↑ Sales ↑

Client Inputs ↑ VAT ↓ Inputs ↓ VAT ↑

Notes: “Collusive evasion” stands for the type of evasion where a transaction is omitted from the books of both the seller and the buyer firm. “Unilateral evasion” stands for the type of evasion where the books of the seller and the buyer reveal discrepancies. Buyers, for whom inputs represent a tax deduction, will tend to overstate the value of the transaction, while sell-ers, for whom the transaction represents a tax liability, will tend to understate its value. The arrows indicate the expected direction of change for the line item in question resulting from an increased audit probability on the treated firm.


II. Study Design, Data, and Empirical Specification

A. Study Design: Letter Message Experiment

Both randomized field studies analyzed in this paper were conducted in collab-oration with the Chilean Tax Authority (Servicio de Impuestos Internos (SII)). A research design diagram can be found in Figure 1. The goal of the Letter Message Experiment is to evaluate the effectiveness of the VAT paper trail across the entire economy in a fully developed, well-functioning VAT system. The tax authority sent out letters aimed at varying the perceived audit probability of randomly chosen firms.14 The goal is to test for differential responses by whether transactions are cov-ered by the VAT paper trail, i.e., whether the transactions are between firms or to the final consumers. As discussed in Section I, if we find that transactions that are subject to a paper trail respond less to an increase in the perceived audit probability, this indi-cates that the paper trail had a preventive deterrence effect prior to the intervention.

A deterrence message was sent to 102,000 randomly selected firms in a stratified sample among most firms in the country.15 The letter is aimed at increasing the per-ceived audit probability by informing firms that they have been randomly selected for analysis and emphasizes that if irregularities are detected, they could be subject to an audit.16 The content of the message was nevertheless factually true—as cer-tified after careful consideration by the tax authority’s legal department—since the tax authority routinely analyzes all firms, and firms may always be audited if irreg-ularities are detected.17

The impact of the letter is measured by comparing the VAT payments of recipi-ent firms to payments by the 306,600 firms of the study sample that did not receive any letter. The idea is to overcome the challenge that it is inherently difficult to determine the degree of evasion at different points in the production chain based on audits. During an ex post audit, it is typically not possible to find out how much VAT was evaded by omitting emission of receipts to final consumers. The innova-tion of this paper is therefore the use of an indirect, “mechanism” experiment to look at firms’ responses as indicators for the underlying level of evasion.18 Since

14 As discussed in Section IIC, the letter content was pretested extensively to ensure its intended interpretation. 15 The sample consists of the universe of Chilean firms that were operating in June 2008, had declared a positive

amount of VAT for at least one month between July 2007 and June 2008, had a valid postal address, and were not included in the Spillover Experiment.

16 The specific language of the letter (translated from Spanish) is as follows: Dear Taxpayer, This is an informational letter and, therefore, does not require that you take any action vis-à-vis the SII. We would like to inform you that, in a process of random selection among micro, small, and medium size enterprises, your firm has been selected for analysis. In the event that any irregularities are detected, you could be summoned for an audit. Our intention is to inform you of the usual actions that the SII carries out, and at the same time to remind you to always declare all purchases, sales and services, and deduct only the credits to which you are entitled.

17 It is important to note that even though used surprisingly frequently in practice, sending out deterrence let-ters which are not backed up by a corresponding increase in the actual audit probability is not a policy that seems sustainable in the long run. As a tool of analysis, it can be used to study differential responses by line item or type of tax payer, both for academic research or to optimize audit strategies (see Pomeranz, Marshall, and Castellon 2014). However, ideally, tax authorities should combine it with real changes in audit policy, since it could otherwise start undermining the agency’s credibility. Nevertheless, the strong response to the second wave of this experiment suggests that the letters do not lose their power very quickly.

18 For further discussion of this approach, see Khwaja and Mian (2011).


the paper trail makes tax evasion easier to observe, all else equal, one would expect an increase in the audit probability to lead to a stronger response for transactions between firms, where a paper trail is present. If, instead, we observe that alerting firms that they are being monitored has less of an effect for these transactions, this suggests that firms had already internalized the higher probability of detection on inter-firm transactions and had reduced evasion on these transactions prior to receipt of the letter, i.e., the paper trail had a “preventive deterrence effect.” Given the large size of the treated group, it is of course plausible that there were spillover effects on the control group. This would bias the estimated effect of the treatment downward since the spillover effects would reduce evasion in the control group as well.

The goal of the Letter Message Experiment is, however, not to measure the over-all effect of the letter on compliance. The intention is to shed light on the effec-tiveness of the paper trail by analyzing how it interacts with the expected audit probability. This is achieved by comparing the responsiveness of line-items in the VAT declaration that are covered by the paper trail, i.e., transactions between two firms—to line items that are not—i.e., sales to final consumers. We can do this both across firms and for different types of transactions within firms. The latter allows holding constant any difference that may exist across firms such as size, risk aver-sion, ease of hiding evasion, etc.

Figure 1. Research Design Diagrams

Letter message experiment Spillover experiment

445,734 small and medium size firmsall active formal firms that are not VAT exempt, not large,not in spillover experiment & have valid postal address

5,600 micro size firms suspected of evasion

LetterssentDec2008

⎧⎪⎨⎪⎩

Deterrenceletter

wave 1

84,618 firms

Tax moraleletter

18,579firms

Placeboletter

18,519firms

Controlgroup

No letter

306,605firms

Auditannouncement

2,800 firms

Controlgroup

no letter

2,800 firms

⎫⎪⎬⎪⎭

Letterdistribution

startsDec2008

LetterssentDec2008

⎧⎪⎨⎪⎩

Deterrenceletter

wave 2

17,413 firms

All 5,600 firms summoned for audit

⎫⎪⎪⎬⎪⎪⎭

AuditstartsMay2009

Trading partner information collected

Obtain information about trading partners from 3 months preceding

audit announcement

Tests for effectiveness of the paper trail

Differential impact by types of transactions and firms

Suppliers and clients of treated

firms

Suppliers and clients of control

group firms

Assesses spillover effects

Comparing VAT filings of clients & suppliers of treated versus control firms

Outcome variables: monthly VAT filings


Finally, the Letter Message Experiment also allows testing predictions about firm size.19 Kleven, Kreiner, and Saez (2009), for example, posit that large firms evade fewer taxes since they run a higher risk that a whistle-blower among their employees informs the government about unreported transactions. We might therefore expect that firm size, similarly to the VAT paper trail, has a preventive deterrence effect that leads to a lower response to an increase in the audit probability. At the same time, smaller firms also tend to have a larger share of sales going to final consumers. Controlling for both firm size and share of final sales, we can get a sense of how much of the differential response by size may be driven by the degree of retail sales.20

To test whether the impact of the letter stems from deterrence, two additional let-ters were each sent to a sample of about 18,500 firms: a tax morale letter aimed at affecting perceived social norms and a “placebo” letter to test whether the effect is driven by the simple fact of receiving mail from the tax authority. The placebo letter informs firms about new features on the tax authority’s website. The tax morale letter contains a message aimed at increasing the perceived social norm of tax compliance. It emphasizes that Chile has one of the highest levels of tax compliance in the world and encourages firms to continue on this path in order to further develop the country.21

B. Study Design: Spillover Experiment

While the Letter Message Experiment studies whether for representative firms across the whole economy, the paper trail interacts in a substitutive way with the audit probability, the Spillover Experiment is designed to show the underlying self-enforc-ing mechanisms in action. It analyzes whether, as predicted by the self-enforcement hypothesis, increased tax enforcement on one firm generates spillovers to its trading partners up the VAT chain. In order to analyze how the self-enforcing mechanism gets triggered by injecting deterrence into the system, the Spillover Experiment focuses on a set of firms where compliance is ex ante expected to be low.

The sample consists of mostly rural, micro size firms with tax declarations that show patterns suggestive of evasion and much lower declared VAT than comparable firms in the same industry. Many of these firms had submitted VAT declarations reg-ularly each month and had not been found guilty of any infractions, but they contin-ually reported sales smaller than their input costs, without going out of business.22 This sample was chosen in order to focus on a segment in the economy where both unilateral and collusive evasion could be expected to be high. The fact that many firms in the sample had zero or negative reported VAT liability created scope for a collusive equilibrium to emerge and to flow up the production chain. Since the

19 The Letter Message Experiment was also used to analyze other firm characteristics not reported in this paper, which are of interest to the tax authority, such as firm age, region, or industry. Based on the analysis of what type of firms are more likely to respond, we developed an instrument to optimize audit strategies (see Pomeranz, Marshall, and Castellon 2014).

20 However, it is important to keep in mind that such cross-firm comparisons have to be interpreted with caution, since in contrast to the within-firm estimates, other unobserved firm characteristics may affect the estimates.

21 Motivational messages have been found to increase voluntary cooperation in some instances. For example, Dal Bó and Dal Bó (2014) find that moral suasion can increase cooperation in the lab, especially when coupled with deterrence, and Fellner, Sausgruber, and Traxler (2013) find that social norm letters increase compliance with broadcast tax obligations for those who live in regions with generally low compliance.

22 Even though sales can temporarily be lower than input costs, for example when firms buy large, costly inputs, over the long run this pattern raises suspicion.


self-enforcement mechanism could be expected to be quite weakly enforced ex ante, increasing deterrence had the potential to jump-start the mechanism.

The intervention of the Spillover Experiment is as follows. Of the 5,600 firms sched-uled for an audit, half of them were randomly selected to receive a preannouncement, which informed them that there was going to be an upcoming audit between June and August 2009.23 The other half did not receive any message. Half a year later, the tax authority started summoning all firms in the sample for an audit. Since the tax authority does not have information on which firms trade with which, information about trading partners was collected during the audits. For the firms the tax authority was able to audit,24 auditors recorded information about the trading partners from the transaction records in the firms’ books of sales and purchases for the three months prior to the mailing of the preannouncement. This made it possible to identify the firms’ main suppliers and clients in a period not yet affected by the treatment. Based on this information, the spillover effects of the audit preannouncement on suppliers and clients of the treated firms can be measured by comparing their declared VAT to the declared VAT of suppliers and clients of the control firms,25 before and after the time when the audit preannouncement was sent out. Finding that trading partners of treated firms increase their declared VAT compared to trading partners of control firms indicates a spillover effect, since whether or not ones’ trading partner was treated is randomly assigned.

C. Implementation and Data

The sample of firms considered in this study consists of the universe of firms in Chile that were operating in June 2008 and had declared a positive amount of VAT for at least one month between July 2007 and June 2008. A subsample of 5,600 firms was selected for the Spillover Experiment, the remainder is in the Deterrence Letter Experiment. The only firms that were excluded from the study were very large firms and firms in the Letter Message Experiment that had invalid postal addresses. The main data consists of information from monthly VAT declarations, starting in January 2008. In addition, I merge this data with firm characteristics such as size, number of employees, industry, etc.

Implementation and Summary Statistics: Letter Message Experiment.—Most let-ters in the Letter Message Experiment were sent in early December 2008, affecting

23 The specific language of the letter (translated from Spanish) is as follows: Dear Taxpayer, This is an informational letter and, therefore, does not require that you take any action vis-à-vis the SII. We would like to inform you that according to control policies carried out by our institution, and under Law 18,320, you will receive a notification that you will be audited at some point between June and August 2009. The purpose of this letter is to give you time to prepare your records for the future audit. Later, you can expect a formal notification letter, which will inform you about which SII office you need to attend, what documents you need to bring and the date of the audit.

24 For a discussion of attrition at the auditing stage see Section IIC below. 25 One potential confounding factor for this estimation strategy could occur if firms that received a prean-

nouncement selectively removed or changed the trading partners in their books. This is discussed in more detail in Section IIC, which provides evidence that the number and characteristics of trading partners reported by treated firms do not differ from those of control firms and discusses why differential manipulations between treated and control firms may not be likely in this setting.


tax declarations starting in November 2008, which are due the following month. A smaller, also randomly chosen second wave was mailed five months later, in order to study whether the effectiveness of the letters decreased over time. The text of all letters was pretested extensively to ensure their intended interpretation. A series of iterative pretests was conducted with almost 100 firm representatives (SME owners, legal representatives, and employees in charge of firms’ tax processes) prior to the mailing. The results showed that the letter strongly increased the perceived proba-bility of audit, and thereby the expected cost of evasion.26 We can therefore interpret the strong, immediate increases in declared taxes following the letters as a response to an increase in the risk of being audited.

In order to increase compliance with treatment assignment in the study sample, we were able to undertake a special procedure with the Chilean Postal Service to exclude firms with invalid postal addresses from both the treatment and the con-trol group of the Letter Message Experiment, leaving a sample of 445,734 firms. Excluding firms with invalid postal addresses from the start allowed us to miti-gate the large reduction of statistical power that ensues when a substantial part of the intent-to-treat sample is not reached. In the sample of firms with valid postal addresses, the share of treatment firms that did not receive the letter was 6 per-cent compared to 26 percent in the full universe. Without this procedure from the postal office we would not have known which firms in the control group would have received a letter that they had been in the treatment group. Firms with invalid addresses would therefore have to be maintained in the estimation sample, leading to strongly reduced statistical precision.

Table 2 presents summary statistics for the Letter Message Experiment, com-pared to the control group. None of the differences are statistically significant at the 10 percent-level.

Firms in the Letter Message Experiment pay an average of 264,000 pesos (about US$500) in monthly VAT, with a median of about 70,000 pesos. The large differ-ence between the mean and the median indicates a very large dispersion in the dis-tribution of tax payments. As discussed below, this dispersion has implications for the empirical specification.

Firms in Chile are categorized into five groups by size, based on their revenues during the preceding tax year: micro, small, medium, large-sized firms, and firms with no sales in the preceding tax year.27 Micro-sized firms are by far the largest group, comprising 74.5 percent of the firms, followed by small firms (18.2 percent), medium size (2.8 percent), and firms with no sales in the preceding year (1.5 per-cent). The remaining 3 percent are new firms that have not yet been classified. Firms are also balanced across the treatment groups with respect to their position in the production chain: 28.8 percent are retailers that sell only to final consumers and

26 The surveys were conducted with firm representatives in an open answer format, while they were waiting their turn for service in different offices of the tax authority throughout the country. When asked “What would you think if you received such a letter,” the modal answer was that the tax authority would audit the firm, and when asked “What would you do if you received such a letter,” firm representatives mentioned a number of things they would do to ensure accurate reporting, such as asking their accountant to review the tax filings.

27 Micro size firms sell less than the equivalent of US$100,000 per year, small firms have sales between US$100,000 and US$1.1 million, medium size between US$1.1 million and US$4.2 million, and large firms over US$4.2 million.


38.2 percent are intermediary firms that sell only to other firms. Overall, the share of sales to final consumers is 45.6 percent.

Implementation and Summary Statistics: Spillover Experiment.—The letters containing the audit preannouncement for the Spillover Experiment were also sent in early December 2008, affecting tax payments starting in November 2008. As discussed above, the sample of the Spillover Experiment consists of mostly rural micro-size firms, which were suspected of evasion. Since many of these small firms were located in remote areas, there was a substantial fraction with no valid postal address. In these cases, the tax authority agreed to deliver the audit preannounce-ment in person to the firms’ location. They were able to reach 96 percent of assigned firms, but there were several weeks of delay for part of them.

Table 3, columns 1 and 2 present summary statistics for the 5,600 firms in the orig-inal sample of the Spillover Experiment. None of the differences between treatment and control group are statistically significant at the 10 percent level. Since this sample

Table 2—Letter Message Experiment: Baseline Summary Statistics and Balance of Randomization

Controlgroup(1)

Differenceto deterrence

(2)

Differenceto tax morale

(3)

Differenceto placebo

(4)

Monthly VAT (mean) 264,029 3,105 305 −10,565(1,871) (3,744) (7,869) (7,472)

Monthly VAT (median) 17,511 −188 −415 −7(115) (231) (491) (462)

Firm age in months 108 −0.32 −0.43 −0.60(0.12) (0.25) (0.51) (0.51)

Percent non-filed declarations 4.3 −0.03 −0.07 −0.02(0.02) (0.05) (0.10) (0.10)

Percent no sales year prior 1.5 −0.05 0.06 −0.01(0.02) (0.04) (0.09) (0.09)

Percent micro size 74.5 −0.04 −0.28 −0.06(0.08) (0.16) (0.33) (0.33)

Percent small size 18.2 0.028 0.102 −0.055(0.07) (0.14) (0.29) (0.29)

Percent medium size 2.8 0.01 0.02 0.07(0.03) (0.06) (0.12) (0.13)

Percent retail firms 28.7 −0.06 −0.28 −0.13(0.08) (0.16) (0.34) (0.34)

Percent intermediary firms 38.2 0.15 0.31 −0.08(0.09) (0.18) (0.37) (0.37)

Percent final sales 45.6 −0.10 −0.29 −0.07(0.08) (0.17) (0.35) (0.35)

Number of firms 306,605 102,031 18,579 18,519

Notes: Each row shows a regression of the pretreatment variable in question on treatment dummies and a constant term. The constant term captures the value for the control group. Monthly VAT winzorized at the top and bottom 0.1 percent to deal with extreme outliers. Columns 2–4 show the difference of the treatment groups to the control group. None of the differences are statistically significant at the 10 percent-level. Monetary amounts are in Chilean pesos, with 500 pesos approximately equivalent to US$1. Robust standard errors in parentheses, clustered at the firm level for all variables except for median tax paid, for which the table shows the result of a median regression for October 2008, the month before the tax payment. All other observations are monthly for ten months prior to treatment (January 2008–October 2008), except for median tax paid, for which observations are averaged over four months prior to treatment.


was selected for having suspiciously high input costs compared to their sales, it is not surprising that their reported sales/input-ratio is low, averaging only 0.67, and their actual mean declared VAT is negative. The mean of −18,452 pesos indicates that on average, these firms declare about US$37 more in tax deduction from input costs than liabilities from sales, and the median VAT declaration is zero. The sample consists of very small, rural firms, mostly in remote areas: all are micro size, and they are among the smallest even within that category, with an average of 2.3 on the official firm size subclassification within micro size, which ranges from 2 to 4.28 Compared to other

28 Given that the official size classification is based on declared sales, and that this sample is suspected of under-declaring true sales, this is likely to be an underestimate of their true size.

Table 3—Spillover Experiment: Baseline Summary Statistics and Balance of Randomization

All firms Audited firms Trading partners

Control group Difference

Control group Difference

Trading partnersof control group Difference

(1) (2) (3) (4) (5) (6)

Monthly VAT (mean) −18,452 −3,849 −8,024 −16,385 1,069,113 29,274(11,370) (12,326) (6,271) (12,988) (82,548) (114,952)

Monthly VAT (median) 0 0 0 0 301,230 10,750(0) (0) (0) (0) (24,656) (34,396)

Firm age in months 131 −0.43 139 −3.33 126 2.01(1.19) (1.69) (2.18) (3.13) (1.77) (2.51)

Percent non-filed 1.09 0.1 0.40 −0.21 1.31 −0.43* declaration (0.13) (0.18) (0.11) (0.13) (1.94) (0.24)Size category 2.28 −0.00 2.34 0.02 5.87 0.065

(0.01) (0.01) (0.02) (0.03) (0.62) (0.9)Percent retail firms 6.82 −0.54 7.27 −1.16 2.26 −0.63

(0.48) (0.66) (0.94) (1.28) (0.49) (0.6)Percent intermediary firms 66.3 −0.46 63 1.01 35.7 −2.37

(0.89) (1.27) (1.76) (2.46) (1.52) (2.13)Percent final sales 15.7 −0.35 19.4 −2.99 22.7 0.15

(0.65) (0.91) (1.35) (1.82) (1.1) (1.46)Sales/input 0.68 −0.01 0.73 −0.03 1.64 −0.15

(0.01) (0.01) (0.02) (0.02) (0.1) (0.11)Percent agriculture 54 0.71 45 5.34** 18.2 1.72

(0.94) (1.33) (1.81) (2.55) (1.32) (1.84)Percent audited 27 0.46 100 0

(0.84) (1.19) (.) (.)Percent suppliers 56.5 −0.0032

(1.46) (2.11)

Number of firms 2,800 2,800 757 770 1,444 1,385

Notes: This table shows summary statistics for the pretreatment period and balance of randomization for three groups: the 5,600 firms in the sample of the Spillover Experiment, the firms that were actually audited, and the trading partners of the audited firms. Each row shows three regressions of the pretreatment variable in ques-tion on a dummy indicating treatment assignment and a constant term: columns 1 and 2 for the firms in the full Spillover Experiment sample, columns 3 and 4 for the audited firms, and columns 5 and 6 for the trading partners. Observations are monthly for ten months prior to treatment (January 2008–October 2008), except for median tax paid, for which observations are averaged over ten months prior to treatment. The constant terms shown in col-umns 1, 3, and 5 capture the values for the control group. Columns 2, 4, and 6 show the difference of the treatment group to the control group. Monetary amounts are in Chilean pesos, with 500 Chilean pesos approximately equiva-lent to US$1. Robust standard errors in parentheses, clustered at the firm level for columns 1 to 4 and at the audited firm’s level for columns 5 and 6.


firms in the country, they also have a smaller share of final sales (16 percent), and are more likely to be in the agricultural sector (54 percent).

The fact that information about the trading partners was obtained during the audits leads to substantial attrition in the final sample for the Spillover Experiment. Due to administrative delays in the delivery of the audit notices, followed by the consequences of a very large earthquake, only about 27 percent of the 5,600 firms were audited and they provided information about 2,829 trading partners. One potential concern of this attrition is that it might introduce selection bias if it creates differences between the treatment and control group within the remaining sample. Since the attrition was mainly driven by the degree to which an area was affected by the earthquake, it is plausibly exogenous to the randomly assigned treatment. Columns 3 and 4 of Table 3 suggest that this is indeed the case. Treatment and con-trol firms do not differ in their probability of being audited and there is no significant difference in the characteristics of treatment and control firms among the audited sample, apart from a somewhat higher proportion of firms in the agricultural sector.

A separate potential issue is that firms that received a preannouncement might have selectively removed or changed the trading partners in their books. There are several reasons why this is unlikely in this case. First, as shown in columns 5 and 6, trading partners of treated firms do not differ from those of control firms, except for a slightly lower share of months in which they failed to submit a declaration. Second, due to the audit method of the Chilean Tax Authority, such differential manipulations are not very likely, since all audited firms, including those in the con-trol group, receive an audit notice in written form weeks before they come into the tax office to get audited. Finally, even if firms had selectively removed their most delinquent trading partners from their books, this would actually lead to a downward biased estimate of the spillover effects.

As the rest of the balance table shows, overall, the trading partners in the Spillover Experiment are substantially larger than the audited firms, both in terms of their VAT paid and their official size category. They have about the same age and a slightly higher share of sales to final consumers, and are much less likely to be in the agri-cultural sector. Their sales/input-ratio is in a much less suspicious range, with an average of 1.6. About 57 percent of trading partners are suppliers of the audited firms, while the rest are clients.

D. Empirical Strategy

The main outcome variable is declared VAT, i.e., 19 percent of declared sales minus declared input costs.29 The dispersion of monthly declared VAT is very large. It ranges from −800 billion pesos (equivalent to US−$1.7 billion) to 16 billion pesos (US$33 million). For illustration, online Appendix Figure A1 shows this very large dispersion, even excluding the top and bottom 5 percent of values. At the same time, there is a large density at zero. Such a large variance and the fat tails of the dis-tribution imply that analyzing the impact of the intervention on the mean of declared

29 If this value is negative because input costs exceed sales in a given month, that amount can be carried over to the next month. All measures used in this paper exclude such carryovers, so that the analysis focuses on the new transactions of the current month. As a robustness check, I also show a specification that includes carryovers.


VAT does not lead to significant results because the resulting variance is extremely large. I therefore use quantile regressions as well as linear probability models for the likelihood that declared VAT is larger than three key thresholds: (i) zero for the extensive margin, (ii) VAT declared in the same month of the previous year, and (iii) the predicted value based on the control group.

The latter two specifications have the advantage of not being sensitive to scale. This is important, given that much of the analysis does not focus on the overall impact of the treatment, but rather on the comparison of the response for different types of transactions or firms. Since the amount in pesos will mechanically be larger in larger types of transactions or firms, and the probability of declaring zero VAT will be smaller, both the quantile regressions and the extensive margin are not appro-priate to analyze differential responses. For such comparisons, measures that cap-tured relative changes are indicated.

Quantile regressions provide an indication of the magnitude of the impact, while being much less sensitive to extreme values than the mean. The specification used throughout is a difference-in-difference approach, comparing treated firms to con-trol firms and pretreatment to post-treatment period. The specification for the quan-tile regressions is therefore

(1) Q τ (VA T it | Z i , t) = α τ + β τ ( Z i · post) + γ τ Z i + ∂ t ,

where Z i is the treatment assignment dummy indicating that a firm is in the treatment group, ∂ t stands for month fixed effects, and Z i · post indicates treatment, i.e., a firm in the treatment group in the post-treatment period.

The linear probability models are analyzed using the following specifications:

(2) T it = α + β( Z i · post) + γ Z i + ∂ t + e it ,

where T it is the binary tax outcome for individual i in month t . The probability of detecting any positive amount, T it = LargerZer o it , captures the extensive margin. However, similar to the quantile regression, this measure will vary with the size of transactions or firms. For analysis of differential responses, a measure captur-ing relative change is required. One specification that satisfies this concern is the linear probability model with the outcome dummy indicating whether declared VAT is higher in the current month compared to the same month a year earlier: T it = VATIncreas e it . This outcome has several benefits compared to alternative measures. First, as opposed to log specifications or count data models, it is applica-ble to variables that include both zeros and negative values, such as is the case for declared VAT. In addition, it provides a relative measure indicating a change in tax declarations compared to the firm’s own history, it is robust against outliers, and at the same time takes into account firms in all parts of the VAT distribution.30

30 One of the alternative specifications is quantile regressions using a normalized version of monthly tax pay-ments in the form of monthly VAT/(pretreatment average VAT). However, this specification is very sensitive to firms with very small pretreatment averages, which end up with very high values when dividing by their pretreatment value. Also, since the median of some line-items is zero, median regressions for these line-items are not informative, and the choice of alternative quantiles becomes to a certain extent arbitrary.


One possible remaining confounding factor could be differential time trends between different types of transactions, which could lead to differences in the proba-bility of an increase compared to the previous year. As a robustness check, I therefore also run a specification with an outcome dummy that indicates whether declared VAT is higher than the predicted value for that firm in that month: T it = Larger Pr edicte d it . The prediction is based on median regressions among the firms in the control group and uses as predictors the firms’ pretreatment VAT payments, as well as those char-acteristics, for which differential treatment effects are evaluated in this paper, such as size and the share of sales to final consumers.31 For robustness, I also implement alternative estimation strategies for nonlinear models following Athey and Imbens (2006) and Blundell and Dias (2009).

When comparing the impact of the letter for different line-items, I use an addi-tional within-firm estimation to hold firm characteristics constant. For example, we can compare sales to input costs by comparing them within each firm and month. An interaction term between the type of transaction and treatment captures the differential impact by line-item. Including the necessary controls, this gives the following regression:

(3) LineItemIncreas e itl = α + β( c i · post) + c i + ∂ t + ϕ( Z i · post · l)

+ η(post · l) + ι l + e itl ,

where l indicates the line-item, c i captures the firm fixed effects controlling for any between-firm variation, and c i · post captures firm fixed-effects times treatment period, to control for any differential trends within the firms. ϕ therefore represents the coefficient of interest: the differential response of line item l for the treatment group in the treatment period.

All regressions of the Letter Message Experiment include both waves of mail-ing. Treatment firms are included until four months after treatment (the time during which the effect of the deterrence letter is the strongest), which is February 2009 for the first wave and June 2009 for the second, and control firms are included until June 2009.32 Since some preannouncements were delivered with delays, a six months post-treatment window is used in the Spillover Experiment. This corre-sponds to an average of four months after delivering of the letter, to be equivalent to the post-treatment window of the Letter Message Experiment.33

Given that the random variation affects only the firms’ perceived audit probabilities, holding everything else constant, following Engel, Galetovic, and Raddatz (2001), I interpret changes in declared income in response to the randomized interventions

31 Predicted medians are used instead of means, since due to the high variance, the predicted mean is again not very informative, and few firms end up close to their predicted mean. The predicting regression is therefore: Q τ (VA T i | preVA T i , X i ) = α τ + β τ preVA T i + X i ′ γ τ , where preVAT is the firm’s average monthly VAT prior to November 2008.

32 Due to the random assignment, dropping one treatment group at an earlier date does not affect the validity of the results. All specifications include month fixed effects.

33 Results from a time-varying instrumental variables approach, aimed at calculating the corresponding Treatment-on-the-Treated effect (available upon request), find similar if slightly larger effects than the Intent-to-Treat results reported in the paper. Robustness checks using four post-treatment months of the Intent-to-Treat specification are similar, if somewhat less statistically significant.


as changes in tax evasion. There may, however, also be a response of real economic activity. The increased tax payments following treatment reduce business profitabil-ity and may lead to increased prices, which, in turn, may decrease demand. All this may lead firms to reduce production. The observed increase in declared VAT may therefore be an underestimate of the reduction in evasion resulting from the treat-ment, since a reduction in production would lead to a decrease in declared VAT.34

III. Results

A. Letter Message Experiment

The Letter Message Experiment examines how the VAT-generated paper trail interacts with tax enforcement for representative firms across Chile, by testing whether the increase in the expected audit probability induced by the deterrence letter has a lower effect on reporting of transactions that are subject to the VAT paper trail—i.e., transactions between two firms—compared to transactions that are not—i.e., sales to the final consumer. This section establishes the overall effectiveness of the deterrence message. It then shows that this increase in the perceived audit prob-ability indeed has a smaller impact where the VAT paper trail is present, even when looking at differential effects within firms, holding all firm characteristics constant.

Overall Effectiveness of Deterrence. —Panel A in Figure 2 shows the impact of the deterrence letter on declared VAT of recipient firms, compared to the control group, which received no letter. The graph shows the percent difference between medians of the treated and control firms in each month. We see a marked jump in tax payments after receipt of the deterrence letter. The median declared VAT increases by about 12 percent and then slowly decreases to reach the same levels as the control group after about 15 months.35 This large response speaks to the credibility of the Chilean Tax Authority in shifting firms’ perceived monitoring risk and also indicates that firms do have scope to increase their tax declarations in the face of heightened deterrence.36

Online Appendix Table A1 confirms the dynamics of the effect of the deterrence letter in regression form. The horizontal line marks the time of the mailing, with t1 indicating the first month affected by the letter and the rows below showing sub-sequent months. Using the binary variables discussed above, it confirms the same pattern shown for the median in the graphical results above: a marked increase after the mailing of the letter and a steady decline thereafter.37

34 If demand is sticky in response to changes in price, the short-term response in evasion might be overestimated (similar to the J-curve phenomenon in trade), while the longer-term response would be underestimated. This means that the decay in the effect of the letters would be slower than it appears in Figure 2.

35 Online Appendix Figure A2 shows a similar pattern for the second wave of mailing. It indicates that even five months after the first wave, the deterrence message is perceived as credible. If anything, the treatment effect is stronger, increasing the median by up to 18 percent. A possible reason is that tax evasion is suspected to have increased in this period due to a downturn in the economy. All regression analyses include both waves of mailing.

36 This is consistent with the findings on the impact of (non-randomized) letter messages by the SII on diesel tax credit claims (Agostini and Martinez 2014).

37 Since the first four months have the strongest overall effect, all subsequent analysis for the Letter Message Experiment is conducted using four post-treatment months. Robustness checks using six post-treatment months, available upon request, show similar effects.


I compare the impact of the deterrence letter to the tax morale and placebo letters to determine whether deterrence drives the effect. Panels B and C of Figure 2 show that in contrast to the deterrence letter, no marked increase is visible at the time of the mailing. The apparent first increase in Panel B happens before mailing, and the second increase almost a year later is very unlikely to be due to the letter. The variance is larger due to the smaller sample size. This comparison shows that it is the content of the deterrence letter that drives the response, not simply the fact of receiving mail from the tax authority.

Table 4 shows the same result in regressions for the mean, median, probability of declaring more than in the same month of the previous year, probability of declaring more than predicted, and probability of declaring any positive amount. All specifi-cations confirm a highly significant impact of the deterrence message, except for the

Mailing of letters−5

0

5

10

Per

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diff

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VA

T

−18 −12 −6 0 6 12

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Panel B. Motivational versus control (median)

Mailing of letters

−5

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10

Per

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diff

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−18 −12 −6 0 6 12

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Panel A. Deterrence versus control (median)

Mailing of letters

−5

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5

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Per

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diff

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T

−18 −12 −6 0 6 12

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Panel C. Placebo versus control (median)

Figure 2. Impact of the Three Types of Letters

Notes: This figure plots the monthly percent difference between the medians of the treatment and the control group for each type of letter: (median VAT treatment group—median VAT control group)/(median VAT control group), normalizing the average of pretreatment months percent difference to zero. The y-axis indicates time, with monthly observations, and zero indicates the last month before the mailing of the letters. The vertical line marks mailing of the letters. The figure shows the first wave of mailing. For the second (much smaller) wave of mailing, see online Appendix Figure A2.


regression using mean VAT, which as expected does not provide statistically signif-icant results.38 The deterrence letter led to a 1,326 peso increase in the median VAT per month, a 7.6 percent increase compared to the baseline median. The probability of declaring more than in the same month of the previous year increased by 1.4 per-centage points, the probability of declaring more than predicted by 1.42 percentage points, and the probability of declaring any positive amount by 0.53 percentage points. All estimates are significant at the 1 percent level.

For robustness, I also report estimates from alternative estimation strategies for the nonlinear models in online Appendix Table A2: Athey and Imbens (2006) for the changes-in-changes estimation on the median VAT and Blundell and Dias (2009) for a nonlinear difference-in-differences estimate of the probability of an increase in VAT compared to the previous year. The results remain qualitatively the same. Finally, online Appendix Table A3, column 1 shows a robustness check that includes the carryovers from previous declarations and also finds a very similar effect.

38 The tax morale letter only has a significant effect on the margin of declaring a positive amount. In line with this, quantile results not shown here find no significant effects overall, except for an increase by those with very low or negative declared VAT. For these firms, receiving a letter about high compliance by others may have a deterrence effect, as it may suggest that the tax authority suspects them of evasion.

Table 4—Letter Message Experiment: Intent-to-Treat Effects on VAT Payments by Type of Letter

MeanVAT

MedianVAT

Percent VAT > previous year

PercentVAT > predicted

PercentVAT > zero

(1) (2) (3) (4) (5)

Deterrence letter × post −1,114 1,326*** 1.40*** 1.42*** 0.53***(2,804) (316) (0.12) (0.10) (0.09)

Tax morale letter × post −1,840 262 0.40 0.30 0.44**(6,082) (666) (0.25) (0.22) (0.20)

Placebo letter × post 835 383 −0.11 −0.19 −0.14(6,243) (687) (0.26) (0.23) (0.20)

Constant 268,810*** 17,518*** 47.50*** 48.27*** 67.30***(1,799) (112) (0.07) (0.07) (0.06)

Month fixed effects Yes Yes Yes Yes YesFirm fixed effects Yes No Yes Yes YesTreatment assignment No Yes No No No

Observations 7,892,076 1,221,828 7,892,076 7,892,076 7,892,076Number of firms 445,734 445,734 445,734 445,734 445,734Adjusted R 2 0.40 0.14 0.28 0.47

Notes: Column 1 shows a regression of the mean declared VAT on treatment dummies, winsorized at the top and bottom 0.1 percent to deal with extreme outliers. Column 2 shows a median regression of average VAT before treat-ment and in four months after each treatment wave. Columns 3–5 show linear probability regressions of the proba-bility of an increase in declared VAT compared to the same month in the previous year, the probability of declaring more than predicted and the probability of declaring any positive amount. Observations are monthly in columns 1 and 3–5 for ten months prior to treatment and four months after each wave of mailing. The four months after the second wave excludes firms treated in the first. Coefficients and standard errors of the linear probability regressions are multiplied by 100 to express effects in percent. Monetary amounts are in Chilean pesos, with 500 Chilean pesos approximately equivalent to $1. Standard errors in parentheses, robust and clustered at the firm level for columns 1 and 3–5.

*** Significant at the 1 percent level. ** Significant at the 5 percent level. * Significant at the 10 percent level.


While the main purpose of sending the deterrence letters was to investigate the deterrence mechanism of the paper trail, the direct impact may be of interest for public policy. Online Appendix Tables A4 and A5 show cost-benefit calculations for the deterrence letter on micro-size firms and find very high return rates (up to 24-fold marginal return).39 However, these estimates do not include fixed costs, as well as potential reputational costs, and should therefore be interpreted with caution (see also footnote 17). For micro-size firms, the overall effect size of the letter mes-sage as a share of the control group mean is 1.9 percent and falls within the range of those observed in other deterrence letter message experiments:40 2.1 percent for non-self-employed middle income individuals and 8 percent for self-employed mid-dle income individuals in Slemrod, Blumenthal, and Christian (2001); 0.5 percent in Kleven et al. (2011); 3.6 percent in Hallsworth et al. (2014).

Interaction with the Paper Trail.—Having established that the tax authority was able to credibly increase the expected audit probability, this section analyzes the differential impact for transactions covered by the VAT paper trail. It first compares different types of transactions overall and then within firms.

Table 5 displays the effect of the deterrence message for the different types of transactions. The first two columns show the two components of the VAT: sales and input costs. By definition, input costs are based on transactions between firms and are therefore subject to a paper trail. If the paper trail has a preventive deterrence effect, one would therefore expect less of a response for input costs than for sales. In line with the self-enforcement hypothesis, columns 1 and 2 indeed show a signif-icant response in sales, but not in input costs. The probability of increasing declared sales compared to the previous year increases highly significantly by 1.17 percent, while there is an insignificant coefficient of 0.16 percent for input costs.41

The Chilean tax forms allow me to further disentangle the effect by distinguish-ing two types of sales: intermediary sales to other firms and final sales to consumers. Columns 3 and 4 show that the effect is again concentrated on the type of transac-tion not covered by the paper trail, the sales to the final consumer. The probability of increasing final sales compared to the previous year goes up by 1.33 percent and is highly significant, while there is only a statistically insignificant effect of 0.12 percent for intermediate sales. Online Appendix Figure A3 shows the effects in graphical form.

The above analysis excludes retail firms that sell only to final consumers, and upstream firms that sell only to other firms. This limits the degree to which the dif-ferential response is driven by cross-firm variation, since by definition, pure retailers cannot respond on intermediate sales or upstream firms on final sales. When includ-ing the entire universe of firms in the analysis (online Appendix Table A6), results are still consistent with the self-enforcing hypothesis. We see a much stronger

39 The cost-benefit analysis focuses on micro-size firms since the values for larger firms are very noisy. 40 This value is calculated for micro-size firms, winsorized at the fifth and ninety-fifth percentile. 41 This of course does not mean that only 1.13 percent of the firms responded to treatment, as firms may for

many other reasons be already above that threshold without the treatment, or far below it. The interpretation of these coefficients is the percent of firms that were pushed over the threshold of last year’s payment due to the increase from treatment. These coefficients unfortunately do not have a very intuitive interpretation, but they are well equipped to show relative responses between different types of firms or transactions.


response on sales than on inputs, and on final sales than on intermediate sales. In this sample, there is some response on inter-firm sales. However, this specification has to be interpreted with caution, since many other characteristics that can affect the response, such as firm size, tax morale, risk aversion, etc. could be correlated with being a retailer or an upstream firm.

Although Table 5 only compares transactions among firms that have both types of sales, we can go one step further in ruling out spurious effects stemming from vari-ation between firms by confirming these findings in a within-firm estimation. The regressions in online Appendix Table A7 follow the specification of equation (3) in Section IID. It uses a dataset that contains an observation for each line item for each firm in a given month. Including firm fixed effects and firm fixed effects times post-treatment period allows comparing the response between different line items within a firm.42 Column 1 compares the effect between sales and input costs, and confirms that the response is clearly concentrated on sales. Column 2 compares the impact between final and intermediary sales, and again finds a much stronger response in final sales.

These results confirm that the finding of a lower response on transactions cov-ered by a paper trail is not driven by heterogeneity between firms. As discussed in Section IB, considering that at a given level of evasion, an audit can be expected to be more effective where a paper trail is present, the fact that the response is lower on these transactions suggests that the paper trail had a preventive deterrence effect, leading to ex ante lower levels of evasion on transactions covered by the paper trail prior to the intervention.

42 To address the large computational demands of two sets of high-dimensional fixed effects, Stata routine reg2hdfe was used (Guimaraes and Portugal 2010).

Table 5—Impact of Deterrence Letter on Different Types of Transactions

Percent sales >

previous year

Percent inputcosts > previous

year

Percent intermediarysales >

previous year

Percent finalsales > previous

year (1) (2) (3) (4)

Deterrence letter × post 1.17*** 0.16 0.12 1.33***(0.22) (0.21) (0.19) (0.21)

Constant 55.39*** 53.25*** 38.37*** 45.04***(0.13) (0.13) (0.12) (0.12)

Month fixed effects Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes

Observations 2,392,529 2,392,529 2,392,529 2,392,529Number of firms 133,156 133,156 133,156 133,156Adjusted R 2 0.25 0.22 0.30 0.32

Notes: Regressions of the probability of the line item (total sales, total input costs, intermediary sales, and final sales) being higher than in the same month the previous year. Sample of firms that have both final and intermediary sales in the year prior to treatment. The four months after the second wave excludes firms treated in the first wave. Coefficients and standard errors are multiplied by 100 to express effects in percent. Robust standard errors in paren-theses, clustered at the firm level.



While we can hold firm characteristics constant, the necessary assumption for this inference is that the lower response is not driven by a difference within firms between final sales and other transactions. There are of course differences between final and intermediate transactions, since it is not randomly assigned whether the client is a consumer or firm. We can also not test directly whether firms interpret the letter to target final sales in particular, though this did not seem to be the case based on the interviews I conducted when pretesting the letters. The Spillover Experiment in Section IIIB will therefore complement the findings of the Letter Message Experiment by showing the underlying mechanism in action.

Interaction with Firm Size.—This section shows how the treatment effect varies with firm size and how this relates to the degree with which firms’ sales are subject to the VAT paper trail. This analysis necessarily implies comparison across firms, as opposed to the VAT paper trail where we can analyze types of transactions within a given firm. Nevertheless, there are interesting correlations.

Table 6 analyzes how the treatment effect varies with both firm size and the share of sales going to final consumers. Column 1 shows that, consistent with the find-ings in the previous section, firms with a larger share of final sales respond more strongly to the deterrence letter. Columns 2 and 3 of Table 6 look at two different measures of firm size: the official two-digit Chilean size classification, based on firms’ revenues in the preceding year, and the log of the number of employees in the pretreatment year. Online Appendix Figure A4 also displays the impact based on three median regressions, one for each of the official Chilean size categories: micro, small, and medium. This is consistent with the idea of Kleven, Kreiner, and Saez (2009) that larger firms evade fewer taxes since collusion is harder with a large num-ber of employees. There may, of course, be many other reasons for this differential response by size.43 With respect to the VAT, the question arises whether the fact that small firms have a higher proportion of retail sales may be driving the differential response by firm size to some extent.

Columns 4 and 5 include interactions of treatment with both the share of final sales and a size measure. The coefficients on the size measures are reduced signifi-cantly. In panel A, looking at the probability of declaring more than in the previ-ous year, coefficients are reduced by about 40 percent, but stay significant, while in panel B, looking at the probability of declaring more than predicted, they are reduced by about two-thirds and are no longer statistically significant. The coeffi-cient on final sales stays highly significant in all specifications.

Since the specification in panel B controls for trends for these different groups of firms over time, it provides the more reliable estimate. This would suggest that almost two-thirds of the larger response in smaller firms can be explained by the degree to which their sales go to final consumers. However, this type of specific magnitude resulting from a horse-race regression between two correlated variables

43 Firms of different sizes may for example vary in their priors about the underlying audit probability, risk aversion, use of other sources of paper trails such as electronic billing, etc. An additional reason for lower evasion may be that in small firms, the person making the evasion decision (e.g., whether or not to give a receipt) is also the residual claimant of the tax money saved, while in large firms, this decision is usually made by an employee who does not benefit directly.


Table 6—Interaction of Firm Size and Share of Sales to Final Consumers

Percent VAT > previous year

(1) (2) (3) (4) (5)

Panel A Deterrence letter × final sales share 1.61*** 1.48*** 1.43***

(0.26) (0.27) (0.26) Deterrence letter × size category −0.17*** −0.10***

(0.04) (0.04) Deterrence letter × log employees −0.45*** −0.29**

(0.11) (0.12)Deterrence letter 0.68*** 2.63*** 1.66*** 1.49*** 0.92***

(0.16) (0.29) (0.13) (0.35) (0.19)Constant 47.53*** 48.87*** 47.50*** 48.89*** 47.53***

(0.08) (0.08) (0.08) (0.08) (0.08)

Final sales share × post Yes No No Yes Yes Size measure × post No Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes YesMonth dummies Yes Yes Yes Yes Yes

Observations 7,308,631 7,116,590 7,340,994 7,084,823 7,308,631Number of firms 406,834 396,135 408,636 394,367 406,834Adjusted R 2 0.14 0.14 0.14 0.14 0.14

Percent VAT > predicted

(1) (2) (3) (4) (5)

Panel B Deterrence letter × final sales share 1.51*** 1.51*** 1.44***

(0.23) (0.25) (0.24) Deterrence letter × size category −0.10*** −0.03

(0.03) (0.04) Deterrence letter × log employees −0.28*** −0.11

(0.10) (0.11)Deterrence letter 0.74*** 2.15*** 1.57*** 1.00*** 0.83***

(0.14) (0.26) (0.12) (0.32) (0.16)Constant 48.48*** 49.79*** 48.26*** 50.01*** 48.48***

(0.08) (0.08) (0.08) (0.08) (0.08)

Final sales share × post Yes No No Yes Yes Size measure × post No Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes YesMonth fixed effects Yes Yes Yes Yes Yes

Observations 7,308,631 7,116,590 7,340,994 7,084,823 7,308,631Number of firms 406,834 396,135 408,636 394,367 406,834Adjusted R 2 0.28 0.26 0.29 0.26 0.28

Notes: Regression of the probability of monthly declared VAT being higher than in the same month of the previous year (panel A) and on being higher than predicted (panel B). Coefficients and standard errors are multiplied by 100 to express effects in percent. Sample includes all firms in the deterrence treatment and in the control group. The four months after the second wave excludes firms treated in the first. Number of observations vary due to missing obser-vations for some variables. Final sales share is not defined for firms with zero sales in preceding year, size category is not available for new firms. Robust standard errors in parentheses, clustered at the firm level.



of course needs to be interpreted with much caution.44 Nevertheless, the results suggest that a significant part of the higher evasion in smaller firms may be driven by a weaker VAT paper trail.

B. Spillover Experiment

The Letter Message Experiment showed that in Chile overall, in general equilib-rium across the whole country, an increase in deterrence generates less of a response on transactions already covered by a VAT paper trail, suggesting that the paper trail has a preventive deterrence effect. The Spillover Experiment complements these findings and is designed to find direct evidence for the underlying self-enforcing mechanism. As discussed in Section IIB above, the experiment injects deterrence into the system in a subsample of firms where compliance is believed to be low, to test for spillovers along the production chain. I measure such spillovers by compar-ing VAT declarations for trading partners of the treated firms to trading partners of the control firms before and after the audit preannouncement.

Table 7 shows the impact of the audit preannouncement for all trading partners. There is a significant increase in declared VAT showing that the preannouncement had compliance effects beyond the treated firm, propagating through the network of their trading partners.45 These results represent the first experimental evidence of tax enforcement generating spillovers to other firms. Given these strong spillover effects, it might be in the interest of tax authorities to take these indirect effects into account when designing an audit strategy. However, the overall spillover effects cannot by themselves establish that the channel is the VAT chain. They could also simply result from a perception of a general increase in the audit risk by firms that are in communication with the treated firms.

Columns 3 and 4 of Table 7 therefore test for the asymmetry in the prediction of the VAT self-enforcement hypothesis. The spillover effects are shown separately for clients and suppliers.46 In line with the predictions, there are strong increases in declared VAT for suppliers, and no significant effects for client firms. This estab-lishes the directionality of the spillover effects up the VAT chain. We can now rule out that the spillovers are simply the results of general conversations about the audit preannouncement with trading partners.

One remaining concern is that this differential effect might be driven by the fact that client and supplier firms are clearly different from each other. I test for robust-ness of this result by including a series of control variables and their interaction with treatment, treatment period, etc. in columns 5 and 6 of Table 7. The included control variables are firm size, the sales-input ratio (a proxy the tax authority uses to assess suspicion of evasion), share of sales to final consumers, and a categorization of whether the firm’s industry is classified by the tax authority as “hard-to-monitor.”

44 If one of the variables is measured with more measurement error than the other, attenuation bias will lead it to look relatively less important.

45 For robustness, I also report nonlinear difference-in-difference estimates following Blundell and Dias (2009) in online Appendix Table A2, columns 7–9.

46 The very small number of trading partners that show up both as a client and as a supplier of some of the audited firms are recorded both as a client and as a supplier. All results are clustered at the level of the audited firm. Any spillovers between the treatment and control group can be expected to lead to a downward bias of the estimates.


The findings remain robust even after inclusion of the control variables, indicating that it is not the different nature of supplier and client firms, but rather their position in the VAT chain that seems to be driving the result.47 Online Appendix Figure A5 shows graphical evidence of the impact of the preannouncement on VAT payments by trading partners.

The findings of the Spillover Experiment provide several insights. First, as pre-dicted by the self-enforcement hypothesis, the built-in paper trail of the VAT leads to spillovers of enforcement up the production chain. Monitoring a firm increases tax payments by its suppliers. Second, this indicates that when taking the whole network of firms into account, the paper trail globally acts as a complement to the audit probability: it augments the effectiveness of an increase in the audit probabil-ity of one firm, by increasing VAT payments by others.

Third, the mere existence of information through the paper trail—not surpris-ingly—is not by itself self-enforcing in an environment where the risk of cross-checks

47 Online Appendix Table A3 shows a robustness check including carryovers from previous VAT declarations. As expected, this introduces more noise, since the firms in the Spillover Experiment had large carryovers from the pretreatment period. The results on the differential spillover effects are robust, though less significant.

Table 7—Spillover Effects on Trading Partners’ VAT Payments

Percent VAT> previous

year

PercentVAT

> predicted


year

PercentVAT

> predicted


year

PercentVAT

> predicted (1) (2) (3) (4) (5) (6)

Audit announcement 2.41** 2.03* × post (1.14) (1.11) Audit announcement 4.28*** 3.92*** 4.14*** 3.83*** × supplier × post (1.54) (1.50) (1.52) (1.52) Audit announcement −0.26 −0.28 −0.14 −0.28 × client × post (1.64) (1.51) (1.67) (1.55) Supplier × post −0.64 0.34 −1.11 0.60

(1.62) (1.59) (1.67) (1.64)Constant 52.07*** 49.06*** 52.07*** 49.06*** 52.75*** 50.11***

(0.95) (0.94) (0.95) (0.94) (0.96) (0.96)

Controls × post No No No No Yes Yes Controls × audit No No No No Yes Yes announcement × post

Month fixed effects Yes Yes Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes Yes Yes

Observations 45,264 45,264 45,264 45,264 44,288 44,288Number of firms 2,829 2,829 2,829 2,829 2,768 2,768Adjusted R 2 0.05 0.11 0.05 0.11 0.05 0.10

Notes: Regressions for trading partners of audited firms. Columns 1, 3, and 5 show the probability of an increase in declared VAT since the previous year, columns 2, 4, and 6 show the probability of declaring more than predicted. The controls in columns 5 and 6 are firm sales, sales/input-ratio, share of sales going to final consumers, and indus-try categorized as “hard-to-monitor.” Observations are monthly for ten months prior to treatment and six months after the audit announcements were mailed. Coefficients and standard errors are multiplied by 100 to express effects in percent. Robust standard errors in parentheses, clustered at the level of the audited firm.



is low. Prior to the audit announcement, self-enforcement was incomplete at best among this sample of firms, even though a VAT system was in place. The small firms in this sample, mostly located in remote areas, were probably correctly anticipating that the risk of the tax authority double-checking their declarations was low. The additional deterrence effect resulting from the preannounced audits was necessary to trigger the effectiveness of the VAT paper trail, indicating that it is only the inter-action of information with deterrence that leads to effective tax enforcement.

IV. Conclusion

This paper investigates the effectiveness of the Value Added Tax in facilitating tax enforcement and sheds light on the role of information and third-party paper trails for taxation. It provides the first micro-empirical evidence for the self-enforcing power of the paper trail in the VAT and for spillovers in tax enforcement through firms’ trading networks more generally, and shows that in line with a growing recent literature, information reporting plays a crucial role for effective taxation.

Two randomized field experiments shed light on the role of the paper trail in the VAT. The Letter Message Experiment looks at the entire economy of Chile and inves-tigates the deterrence effect of the VAT paper trail, incorporating the general equilib-rium effects of this long established policy. It finds that holding firm characteristics constant, transactions that are already subject to the VAT paper trail respond much less to an increase in the perceived audit probability. Since for a given level of evasion, an audit can be expected to be more effective where a paper trail is present, the fact that the response is lower suggests that the paper trail had a preventive deterrence effect, leading to lower levels of evasion on transactions covered by the paper trail. In line with predictions of Kleven, Kreiner, and Saez (2009), the Letter Message Experiment also finds a stronger response for smaller firms. Controlling for the degree of retail sales reduces this differential response considerably, suggesting that a significant part of the higher evasion among smaller firms may be driven by a weaker paper trail.

The Spillover Experiment looks at the underlying dynamic that creates the pre-ventive deterrence effect of the paper trail, and is designed to show the self-enforcing mechanism in action. It finds that as predicted by the self-enforcement hypothesis, increasing the audit probability of firms suspected of evasion generates spillovers up the VAT paper trail that lead to an increase of their suppliers’ tax payments. These multiplier effects indicate that globally the VAT paper trail acts as a complement to the audit probability.

The combined findings also show that while in Chile overall, the VAT paper trail seems to be highly effective, the mere existence of a VAT system, in the absence of credible deterrence, does not lead to “self-enforcement”—as exemplified by the low compliance among the sample of the Spillover Experiment prior to the intervention. It is the interaction of information with deterrence that leads to effective tax enforcement.

These results have a number of implications for public finance in develop-ing countries and for tax policy in general. First, and most broadly, in line with findings from the literature on corruption and illegal capture of public funds, such as Reinikka and Svensson (2005), the conclusions confirm that verifiable paper trails on financial flows can provide a powerful tool, rendering misappropriation of funds more difficult. More modern instruments, such as aerial photography and


digital records, have large potential to increase the degree of verifiable information (Casaburi and Troiano forthcoming).

Second, the results are informative for the choice of tax instruments. They sug-gest that forms of taxation such as the VAT, which leave a stronger paper trail and thereby generate more information for the tax authority, provide an advantage for tax collection over other forms of taxation, such as a retail sales tax. Other mech-anisms that provide information to the government, such as online billing systems or electronic receipts, as recently introduced by Brazil and Kenya, may have high returns. Further research is required to investigate the effectiveness of such mecha-nisms, as well as the dimensions of generalizability of these findings. For example, the Chilean Tax Authority has a reputation for being highly effective and having low levels of corruption. On one hand, the paper trail may be more important in high corruption environments as it reduces the discretion of tax officials (e.g., Baurer 2005). At the same time, the paper trail may be less effective where enforcement can be circumvented by paying off the tax auditor.

Third, the spillover effects are relevant for the design of optimal audit strategies. When choosing which firms to audit, a tax authority may not only want to consider the expected impact on the audited firm, but also the multiplier effect through a firm’s trading network. In particular, the higher response in final sales and spillovers along the supply chain suggest that increasing the audit probability at the end of the production chain is beneficial both because it yields higher direct returns and because the spillovers will transmit the effect up the production chain. At the same time, enforcement at the final sales stage is also more costly, given the absence of a paper trail and the smaller average firm size. Further research is required to analyze how to optimally allocate audit probabilities to different nodes in the network.

Fourth, as Emran and Stiglitz (2005) point out, the VAT is only effective among firms in the formal sector, and a heavy reliance on the VAT can therefore increase the inter-sectorial distortions between formal and informal sectors. De Paula and Scheinkman (2010) find that where the VAT is present, formalized firms tend to trade with other formalized firms, since these can provide them with receipts that allow them to deduct the input costs from VAT payments, while informal firms tend to trade among themselves. Combined with the spillover findings, this suggests that enforcing formalization at the final stage of production might potentially contribute to formalizing entire production chains.

Fifth, the differential enforcement through the paper trail at different production stages leads to differences in effective tax rates and potential distortions in the mar-ket. If the evasion rate is higher for downstream firms, a flat VAT rate will result in upstream firms paying a higher effective tax rate. This may lead to incentives for increased vertical integration at the last production stage and can create distortions in production between intermediary goods and final goods. On the other hand, if small firms can evade more, this may lead firms to stay inefficiently small to reduce their effective tax burden. Further research is required to investigate whether such distortions will be economically significant and warrant a revision of the frequently postulated recommendation that, putting aside redistributive considerations, a flat nominal VAT rate is optimal (e.g., Ebrill et al. 2001).

Finally, the results suggest a possible explanation for the differences in tax evasion between developed and developing economies. In many developing countries, home


production plays an important role, gains from trade and division of labor are rela-tively small, and production chains tend to be shorter. Moreover, if gains from trade are small, division of labor may not only be low, but also more elastic with respect to taxation. If the division of labor leads to transactions between agents, which—in contrast to home production—are traceable by the tax authority, small taxes may be enough to discourage such divisions and thereby erode the traceable tax base. All these factors may make it harder for developing countries to develop an effective tax system, since they reduce the number of transactions that can lead to verifiable paper trails—through the VAT or through other forms of third-party reporting.

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No Taxation without Information: Deterrence and Self ... · No Taxation without Information: Deterrence ... 1Information constraints have been a key feature of models in the optimal